Dynamic economic load dispatch using hybrid swarm intelligence based harmony search algorithm

This paper presents the hybrid harmony search algorithm with swarm intelligence (HHS) to solve the dynamic economic load dispatch problem. Harmony Search (HS) is a recently developed derivative-free, meta-heuristic optimization algorithm, which draws inspiration from the musical process of searching for a perfect state of harmony. This work is an attempt to hybridize the HS algorithm with the powerful population based algorithm PSO for a better convergence of the proposed algorithm. The main aim of dynamic economic load dispatch problem is to find out the optimal generation schedule of the generators corresponding to the most economical operating point of the system over the considered timing horizon. The proposed algorithm also takes care of different constraints like power balance, ramp rate limits and generation limits by using penalty function method. Simulations were performed over various standard test systems with 5 units, 10 units and 30 units and a comparative study is carried out with other recently reported results. The findings affirmed the robustness and proficiency of the proposed methodology over other existing techniques.

Research highlights
► We formulated hybrid harmony search with swarm intelligence (HHS) for solving non-convex problem.
► The proposed algorithm applied to dynamic economic dispatch to minimize the fuel cost of generators over the scheduling horizon.
► The HHS algorithm applied to 5 units, 10 units and 30 units system and compared with other reported results.
► The convergence and robustness of HHS algorithm is better than other reported algorithm.